Top Senior Machine Learning Jobs in Rochester, NY

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Lead Bioinformatics AI Scientist will lead AI and GenAI R&D initiatives to develop advanced clinical testing and genomic data analysis platforms, leveraging expertise in bioinformatics and machine learning.

As a Senior Fullstack Engineer, you'll architect and build a high-concurrency auction engine, leveraging AI for enhanced user experiences and system reliability.

The Senior Data Scientist will develop scalable ML models, analyze large datasets for insights, and collaborate with teams to enhance business performance through data-driven solutions.

The Product Manager will identify process improvements and innovations, utilize automation and AI, and manage the product lifecycle to enhance productivity and deliver business value.

The Senior Engineering Manager at Planet leads the engineering team, focusing on delivering products for Defense Intelligence. Responsibilities include mentoring engineers, refining processes, and collaborating across teams for effective deployment of technology.

Lead strategy, roadmap, and delivery for Tekmetric's SaaS product for auto repair shops. Own user research, AI/ML product initiatives, cross-functional alignment, go-to-market coordination, and measurement of business outcomes. Train internal teams and iterate on features from concept through launch and optimization.

Lead product strategy and execution for data and AI platforms, driving GenAI/LLM initiatives, cross-functional collaboration, responsible AI governance, experimentation (A/B testing), measurement of model impact, and mentoring product teams to embed scalable ML capabilities into clinical and member experiences.

Lead the development of deep learning models for email data, optimize models, design evaluation frameworks, integrate products, and mentor junior researchers.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Design, implement, and scale ML-based solutions for search and advertising; define data collection, evaluation, and production serving strategies; analyze data to inform development; communicate cross-functionally; produce technical reports; and stay current with advances in LLMs, vision models, and generative AI.

Design, build, and scale backend systems and APIs for high-transaction consumer products. Collaborate with product, credit, compliance, support, and analytics teams. Contribute to code reviews, technical planning, security, and operational excellence. Mentor peers and promote engineering best practices.

As a Senior Machine Learning Engineer, you will enhance diffusion models, conduct research, collaborate on system implementations, and communicate findings effectively.

The Senior Customer Success Manager drives revenue growth by ensuring customer satisfaction, building strong relationships, managing renewals, and promoting product solutions aligned with client goals.

Design and implement data-centric cybersecurity solutions: develop ML algorithms and automation for security tools; discover, parse, map, and transform legacy RMF artifacts into OSCAL; migrate and analyze security data; reproduce dashboards/workflows in eGRC; collaborate with Professional Services; produce migration assessments and reports.

Lead BI analytics and governance for client accounts: manage BI analysts, deliver dashboards and reports, oversee data mapping, modeling, quality, and platform initiatives (Power BI/Databricks), advise stakeholders, drive analytics roadmap, and apply advanced analytics and ML to optimize workplace and portfolio insights.

Design, build, and operate production-grade AI systems using ML, LLMs, RAG, and agentic workflows. Define evaluation strategies, implement data/retrieval/orchestration layers, apply MLOps/LLMOps, and partner with stakeholders to prioritize, monitor, troubleshoot, and improve AI solutions balancing quality, latency, cost, reliability, and maintainability.

Lead the integration of AI and digital solutions in manufacturing processes, driving adoption and measurable impact on efficiency, quality, and performance.

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

Build and scale core components of an end-to-end proteomics software stack (LIMS, data pipelines, web portal). Design agentic backends and AI-augmented tooling, develop analysis algorithms and lab integrations, deploy cloud IaC and CI/CD, write tests and monitoring, and collaborate with R&D, operations, and customers to productionize tools for high-throughput proteomics.

The Principal Product Manager - Growth will lead growth initiatives, focusing on user engagement, retention, and the use of AI to enhance product strategies and experiences.

The Senior Technical Architect will lead AI SDLC transformations, create architectural solutions, mentor teams, and drive innovation in regulated industries.

As a Regional Sales Director, you'll lead a sales team, develop business plans, and drive sales growth by managing complex cycles and nurturing talent.

Design and scale fraud-mitigation strategies for buyer, seller, and account fraud across Stripe products. Monitor portfolios, identify and predict risky behavior, propose controls, automate workflows, collaborate with Product/Engineering/Data Science, and educate users to minimize losses while enabling growth.

Lead product lifecycle for internal PaaS and Data-as-a-Service offerings focused on SRE and data engineering. Drive system reliability (99.99% availability), scaling strategies, GCP cost optimization, BigQuery/table and ETL performance, AI/ML enablement, and data governance/compliance across cross-functional teams.